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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+  - unconditional-image-generation
+tags:
+  - microscopy
+  - electron-microscopy
+  - HAADF-STEM
+  - nanoparticles
+  - simulation
+  - materials-science
+  - webdataset
+size_categories:
+  - 100K<n<1M
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: "train-*.tar"
+---
+
+# Nanoparticle Size Estimation Dataset (WebDataset)
+
+100,000 simulated HAADF-STEM images of nanoparticles with three image variants per sample (raw simulation, normalized, and CycleGAN style-transferred), paired with per-structure metadata including atomic coordinates, morphology, and simulation parameters.
+
+## Dataset Description
+
+Synthetic HAADF-STEM images of Pt nanoparticles on various support interfaces, generated for nanoparticle size and morphology prediction. Each sample includes the raw simulation output, a set-normalized version, and a CycleGAN-transferred version that emulates experimental noise characteristics. Associated with the paper [Nanoparticle size estimation](https://pubs.acs.org/doi/10.1021/acs.nanolett.4c06025).
+
+Original data: [Zenodo record 14608502](https://zenodo.org/records/14608502)
+
+## Format
+
+WebDataset format: 20 TAR shards (~1 GB each), 19 GB total.
+
+Each sample in a shard contains:
+- `{idx:06d}.sim_raw.npy` — raw simulated HAADF-STEM image (128x128, float32)
+- `{idx:06d}.sim_norm.npy` — set-normalized simulation (128x128, float32)
+- `{idx:06d}.cyclegan.npy` — CycleGAN style-transferred image (128x128, float32)
+- `{idx:06d}.json` — metadata
+
+### Metadata Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `sample_id` | int | Original sample index |
+| `original_filename` | string | Original .npy filename |
+| `width` | int | Image width (128) |
+| `height` | int | Image height (128) |
+| `pixel_size` | float | Pixel size in Angstroms |
+| `beam_offset_x` | float | Beam offset in x |
+| `beam_offset_y` | float | Beam offset in y |
+| `particle_rotation` | float | Particle rotation angle (radians) |
+| `structure_type` | string | Nanoparticle morphology (cluster, wulff, random, etc.) |
+| `support_interface` | string | Support surface orientation (e.g., 111, 100, random) |
+| `particle_interface` | string | Particle surface orientation |
+| `element` | string | Atomic species (Pt) |
+| `subset` | string | Dataset subset label (e.g., AC_111_111) |
+| `n_atoms` | int | Number of atoms in the structure |
+| `raw_min` | float | Minimum pixel intensity (raw image) |
+| `raw_max` | float | Maximum pixel intensity (raw image) |
+| `raw_mean` | float | Mean pixel intensity (raw image) |
+| `raw_std` | float | Std dev of pixel intensity (raw image) |
+
+### Image Properties
+
+- **Count:** 100,000 samples (300,000 images total across 3 variants)
+- **Format:** NumPy arrays (.npy), float32
+- **Resolution:** 128x128
+- **Modality:** Synthetic HAADF-STEM
+- **Element:** Pt nanoparticles
+- **Morphologies:** cluster, wulff, random
+
+## Usage
+
+```python
+import webdataset as wds
+import numpy as np
+from torch.utils.data import DataLoader
+
+url = "path/to/nanoparticle_wds/train-{0000..0019}.tar"
+dataset = wds.WebDataset(url).decode().shuffle(1000)
+dataloader = DataLoader(dataset, batch_size=64, num_workers=4)
+
+for sample in dataloader:
+    raw_image = sample[".sim_raw.npy"]
+    norm_image = sample[".sim_norm.npy"]
+    cyclegan_image = sample[".cyclegan.npy"]
+    metadata = sample[".json"]
+```
+
+## Source
+
+Original data from [Zenodo record 14608502](https://zenodo.org/records/14608502). Associated paper: [Nano Letters (2024)](https://pubs.acs.org/doi/10.1021/acs.nanolett.4c06025).
+
+## License
+
+CC-BY-4.0

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